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Synopsis
This book presents the first comprehensive treatment of neural networks from an engineering perspective. Thorough, well-organized, and completely up-to-date, it examines all the important aspects of this emerging technology. --This text refers to an out of print or unavailable edition of this title. From the Back Cover
KEY BENEFIT:Fluid and authoritative, this well-organized book represents the first comprehensive treatment of neural networks from an engineering perspective, providing extensive, state-of-the-art coverage that will expose readers to the myriad facets of neural networks and help them appreciate the technology's origin, capabilities, and potential applications.KEY TOPICS:Examines all the important aspects of this emerging technolgy, covering the learning process, back propogation, radial basis functions, recurrent networks, self-organizing systems, modular networks, temporal processing, neurodynamics, and VLSI implementation. Integrates computer experiments throughout to demonstrate how neural networks are designed and perform in practice. Chapter objectives, problems, worked examples, a bibliography, photographs, illustrations, and a thorough glossary all reinforce concepts throughout. New chapters delve into such areas as support vector machines, and reinforcement learning/neurodynamic programming, plus readers will find an entire chapter of case studies to illustrate the real-life, practical applications of neural networks. A highly detailed bibliography is included for easy reference. MARKET:For professional engineers and research scientists. Back to General
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